Principal Machine Learning Engineer, AI Inference

Principal Machine Learning Engineer Focused on vLLM

At Red Hat we believe the future of AI is open and we are on a mission to bring the power of open-source LLMs and vLLM to every enterprise. Red Hat Inference team accelerates AI for the enterprise and brings operational simplicity to GenAI deployments. As leading developers, maintainers of the vLLM project, and inventors of state-of-the-art techniques for model quantization and sparsification, our team provides a stable platform for enterprises to build, optimize, and scale LLM deployments. As a Principal Machine Learning Engineer focused on vLLM, you will be at the forefront of innovation, collaborating with our team to tackle the most pressing challenges in model performance and efficiency. Your work with machine learning and high performance computing will directly impact the development of our cutting-edge software platform, helping to shape the future of AI deployment and utilization. If you are someone who wants to contribute to solving challenging technical problems at the forefront of deep learning in the open source way, this is the role for you. Join us in shaping the future of AI!

What you will do:

• Write robust Python and C++, working on vLLM systems, high performance machine learning primitives, performance analysis and modeling, and numerical methods.
• Contribute to the design, development, and testing of various inference optimization algorithms.
• Participate in technical design discussions and provide innovative solutions to complex problems.
• Give thoughtful and prompt code reviews.
• Mentor and guide other engineers and foster a culture of continuous learning and innovation.

What you will bring:

• Extensive experience in writing high performance code for GPUs and deep knowledge of GPU hardware.
• Strong understanding of computer architecture, parallel processing, and distributed computing concepts.
• Experience with tensor math libraries such as PyTorch.
• Deep understanding and experience in GPU performance optimizations.
• Experience optimizing kernels for deep neural networks.
• Experience with high-performance networking protocols and technologies including UCX, RoCE, InfiniBand, and RDM.
• Strong communications skills with both technical and non-technical team members.
• BS, or MS in computer science or computer engineering or a related field. A PhD in a ML related domain is considered a plus.

The salary range for this position is $189,600.00 - $312,730.00. Actual offer will be based on your qualifications.

Red Hat determines compensation based on several factors including but not limited to job location, experience, applicable skills and training, external market value, and internal pay equity. Annual salary is one component of Red Hat's compensation package. This position may also be eligible for bonus, commission, and/or equity.

Red Hat (https://www.redhat.com/) is the world's leading provider of enterprise open source software solutions, using a community-powered approach to deliver high-performing Linux, cloud, container, and Kubernetes technologies.

Benefits include comprehensive medical, dental, and vision coverage, flexible spending accounts, health savings account, retirement 401(k) with employer match, paid time off and holidays, paid parental leave plans, leave benefits including disability, paid family medical leave, and paid military leave, and additional benefits including employee stock purchase plan, family planning reimbursement, tuition reimbursement, transportation expense account, employee assistance program, and more!

Inclusion at Red Hat is built on the open source principles of transparency, collaboration, and inclusion, where the best ideas can come from anywhere and anyone. Our aspiration is that everyone experiences this culture with equal opportunity and access, and that all voices are not only heard but also celebrated.

Red Hat is proud to be an equal opportunity workplace and an affirmative action employer. We review applications for employment without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, citizenship, age, veteran status, genetic information, physical or mental disability, medical condition, marital status, or any other basis prohibited by law.

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